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This paper deals with real time Three-Axis Magnetometers (TAM) calibration, applied to gun-launched spinning projectiles. The first part of this note present a new model used for real time estimation without any knowledge of the attitude of the projectile. Then the main contribution is a new simple and useful filter used for parameters estimation. The latter is formulated in the framework of a traditional...
A new version of the extended Kalman filter (EKF) is proposed for nonlinear systems possessing symmetries. Instead of using a linear correction term based on a linear output error, it uses a geometrically adapted correction term based on an invariant output error; in the same way the gain matrix is not updated from of a linear state error, but from an invariant state error. The benefit is that the...
This paper presents a method to build the large-scale indoor maps by means of extended Kalman filter (EKF) localization which explores the statistical distribution of noise parameters. As typical method in many robot localization applications, EKF localization has shown considerable success history to locate the position of the robot. However, EKF has also lack which can degrade its performance, especially...
This paper describes the adaptive extended Kalman filtering which is applied to low-cost MEMS IMU/GPS integration. Unmanned Aerial Vehicles are versatile flying machine capable of handling both military and civilian missions. The availability of low-cost MEMS IMU has made it possible to construct inexpensive, integrated systems for usage in UAV applications. The adaptive extended Kalman filtering...
In this paper we show how to accurately track position and orientation of a mobile robot using positioning only RF ultrasound transceiver system and dead-reckoning. The solution is based on geometrical displacement of the positioning device from the axis of rotation of the robot which brings dependency in position of the device and robot's orientation and enables the correction of the absolute orientation...
Localizing a vehicle consists in estimating its state by merging data from proprioceptive sensors (inertial measurement unit, gyrometer, odometer, etc.) and exteroceptive sensors (GPS sensor). A well known solution in state estimation is provided by the Kalman filter. But, due to the presence of nonlinearities, the Kalman estimator is applicable only through some alternatives among which the extended...
Navigation, guidance and control for small space vehicles require inertial measurement sensors which are small, inexpensive, low power, reliable and accurate. Micro inertial sensors, such as MEMS gyroscopes, can provide small, inexpensive, low power devices; however, the accuracy of these devices is insufficient for many space applications. Signal processing methods can be used to provide the necessary...
This paper is concerned with the estimation problem for discrete-time stochastic linear systems with multiple packet dropouts. Based on a recently developed model for multiple-packet dropouts, the original system is transferred to a stochastic parameter system by augmentation of the state and measurement. The optimal full-order linear filter of the form of employing the received outputs at the current...
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